Mathematics and Statistics with a Year Abroad

Mathematics and statistics together cover the full range of quantitative reasoning, from pure mathematical theory to the application of statistical methods to real data. Mathematics develops your ability to reason logically, construct proofs, and work with abstract structures. Statistics develops your ability to collect, describe, and draw inferences from data, and to make decisions under uncertainty in a rigorous and principled way.

In an era defined by the proliferation of data, the combination of deep mathematical knowledge and strong statistical competence is among the most sought-after skill sets in the graduate market.

At the University of Liverpool, this four-year full-time programme includes a year abroad, giving you the opportunity to study at one of the university's partner institutions around the world, following a mixture of culture and discipline-related modules. This international year enriches your academic development and broadens your experience in ways that are genuinely valued by employers. You will study core areas of pure and applied mathematics, including analysis, algebra, differential equations, and numerical methods, alongside statistical theory, probability, data modelling, and inference.

You will develop strong computational skills and the ability to use mathematical and statistical software in solving real problems, which increasingly defines professional practice in quantitative fields.

The typical entry tariff is 136 UCAS points, and the degree is studied full time. Graduates from mathematics and statistics programmes are among the most employable in any field. Careers in finance, insurance, data science, government statistics, actuarial work, management consultancy, scientific research, and software development are all common paths.

The analytical rigour the degree develops is valued in virtually any field that requires quantitative thinking. Further study options include master's degrees and doctoral programmes in mathematics, statistics, data science, and quantitative finance.